#2: What You Need to Know About Machine Learning Algorithms and Why You Should Care

Yael Gavish
Jul 25, 2017 · 14 min read

Algorithms, Models and Data

Types of “Learning”

Supervised Learning

Unsupervised Learning

Semi-supervised Learning

Reinforcement Learning

Other Common “Buzzwords” Worth Knowing

How the Problem Affects the Solution (And Some More Key ML Concepts)

Algorithm Selection

Feature Selection

Objective Function Selection

Explainability and Interpretability

Modeling and Performance Measurement Pitfalls PMs Should Watch Out For

Overfitting

Overfitting illustration

Precision, Recall and the Tradeoff Between Them

The Often Misleading Model Accuracy Metric

Averaging Metrics and Imbalanced Training Data


Yael Gavish

Written by

Entrepreneur, startup advisor · Formerly product @ Facebook, Yahoo!, multiple startups · linkedin.com/in/yaelgavish

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